diff --git a/README.md b/README.md index 207ea0a..7493ccb 100644 --- a/README.md +++ b/README.md @@ -1,171 +1,155 @@ + +> [!NOTE] +> 本文档由 WeHub 基于上游 README 翻译整理，属于社区翻译，非官方中文文档。 +> [English](./README.en.md) · [原始项目](https://github.com/makerspet/oomwoo) · [上游 README](https://github.com/makerspet/oomwoo/blob/HEAD/README.md) +> 原作者、版权与许可证归属以原始项目及本仓库 LICENSE 文件为准。 +
# OOMWOO -*Open-source robot vacuum you build yourself.* +*可自行搭建的开源扫地机器人。* -Clean well · Hackable · Raspberry Pi · ROS2 · Home Assistant · 2D LiDAR · 3D printed · ESP32 · Arduino +扫得干净 · 可二次开发 · Raspberry Pi · ROS2 · Home Assistant · 2D LiDAR · 3D 打印 · ESP32 · Arduino ![License](https://img.shields.io/badge/license-Apache--2.0-blue) ![Status](https://img.shields.io/badge/status-early%20development-orange)
-## What is this? +## 这是什么？ -OOMWOO is an *open-source home robot vacuum* you can build yourself, made for the -Raspberry Pi, ROS2, Home Assistant, and 3D-printing communities. It uses an -affordable 2D LiDAR to map your home and navigate on its own. Local, no -cloud required for regular functionality, no vendor lock-in. Follow us building in public +OOMWOO 是一款可自行搭建的*开源家用扫地机器人*，面向 Raspberry Pi、ROS2、Home Assistant 和 3D 打印社区打造。它使用价格亲民的 2D LiDAR 绘制家中地图并自主导航。本地运行，日常功能无需云端，无厂商锁定。欢迎关注我们公开搭建的过程 [Discord](https://discord.gg/3y2JKz5T25) | [X](https://x.com/@0OMWO0) | [Instagram](https://www.instagram.com/oomw0o/) | [Facebook](https://www.facebook.com/profile.php?id=61591466775035) | [Reddit](https://www.reddit.com/r/oomwoo/) | [newsletter](https://stats.sender.net/forms/bo2rAK/view) | [YouTube](https://www.youtube.com/@makerspet) | [oomwoo.com](oomwoo.com) | [Tutorials](https://makerspet.com/learn/) -Reference design images - this is approximately how the finished design will look: +参考设计图——成品大致将呈现如下外观： ![Reference robot vacuum cleaner top](./assets/vacuum_model_top.webp) ![Reference robot vacuum cleaner bottom](./assets/vacuum_model_bottom.webp) ![Reference robot vacuum cleaner - top cover removed](https://github.com/makerspet/oomwoo/blob/main/assets/vacuum-no-top-back.webp) -## Goals +## 目标 -- Affordable, fully open hardware, software and firmware -- Home appliance product quality - not a throwaway build -- Easy to build, with step-by-step zero-to-hero instructions -- 2D LiDAR mapping and autonomous navigation (ROS2 / Nav2) -- Native Home Assistant integration for local control -- 3D-printable, documented, and hackable chassis -- Buildable from parts you source yourself -- Local, no cloud required for regular functionality -- Optional extra functionality when connected cloud -- Apps on top of ROS2 to customize vacuum operation -- Stretch goal: App store -- Stretch goal: LeRobot integration, OpenClaw +- 价格实惠，硬件、软件和固件完全开源 +- 家用电器级品质——不是一次性搭建项目 +- 易于搭建，提供从零到精通的逐步教程 +- 2D LiDAR 建图与自主导航（ROS2 / Nav2） +- 原生 Home Assistant 集成，支持本地控制 +- 3D 可打印、有文档且可二次开发的车体 +- 可使用自行采购的零件搭建 +- 本地运行，日常功能无需云端 +- 连接云端时可获得可选的额外功能 +- 基于 ROS2 的应用，可自定义清扫行为 +- 延伸目标：应用商店 +- 延伸目标：LeRobot 集成、OpenClaw -*v0 target: bare-bones build:* +*v0 目标：精简版搭建：* -- 3D-printed chassis -- ROS2 Gazebo sim -- LiDAR with manual SLAM -- ROS2 on Raspberry Pi 5 AND/OR ESP32 running micro-ROS with ROS2 on local PC - decision TBD +- 3D 打印车体 +- ROS2 Gazebo 仿真 +- 配备 LiDAR 的手动 SLAM +- 在 Raspberry Pi 5 上运行 ROS2，和/或在 ESP32 上运行 micro-ROS 并在本地 PC 上运行 ROS2——待确定 -Open Source Deliverables: +开源交付物： -- [x] [Software development environment](https://github.com/makerspet/oomwoo-install), robot [description package](https://github.com/makerspet/oomwoo-one/) and [tutorials](https://makerspet.com/blog/simulate-oomwoo-one-robot-vacuum-in-gazebo-with-ros-2/) (ROS2) -- [x] Placeholder real [vacuum cleaner](https://github.com/makerspet/proscenic-m6pro) and [tutorials](https://makerspet.com/blog/tutorial-connect-robot-vacuum-cleaner-to-ros-2-proscenic-m6-pro/) (temporary while OOMWOO is being designed) -- [ ] [Bill of materials (BoM)](BOM.md) (in progress) -- [ ] 3D-printable files -- [ ] Firmware -- [ ] Motor drivers and sensors [I/O PCB](https://github.com/makerspet/oomwoo-io-board) -- [ ] Build, setup, bringup and troubleshooting [instructions](BUILD_INSTRUCTIONS.md) -- [ ] Demo video(s) +- [x] [软件开发环境](https://github.com/makerspet/oomwoo-install), robot [description package](https://github.com/makerspet/oomwoo-one/) and [tutorials](https://makerspet.com/blog/simulate-oomwoo-one-robot-vacuum-in-gazebo-with-ros-2/) (ROS2) +- [x] 占位用真实[扫地机](https://github.com/makerspet/proscenic-m6pro) and [tutorials](https://makerspet.com/blog/tutorial-connect-robot-vacuum-cleaner-to-ros-2-proscenic-m6-pro/) (temporary while OOMWOO is being designed) +- [ ] [物料清单（BoM）](BOM.md) (in progress) +- [ ] 3D 可打印文件 +- [ ] 固件 +- [ ] 电机驱动与传感器 [I/O PCB](https://github.com/makerspet/oomwoo-io-board) +- [ ] 搭建、配置、启动与故障排查[说明](BUILD_INSTRUCTIONS.md) +- [ ] 演示视频 -## Contributing +## 参与贡献 -Would you like to contribute? See [CONTRIBUTING](docs/CONTRIBUTING.md) for the full guide. +想要参与贡献？完整指南请参阅 [CONTRIBUTING](docs/CONTRIBUTING.md)。 -OOMWOO is organized to built by the community, massively *in parallel*. -The vacuum and its software are subdivided into [modules](#requests-for-contributions), see list below. +OOMWOO 采用社区大规模*并行*搭建的组织方式。 +扫地机及其软件划分为多个[模块](#requests-for-contributions)，见下方列表。 -A volunteer picks whatever module she wants and works on it whenever she wants. -For *code and simulation* modules she builds her package in her *own repo* and sends -a short PR *linking* it from the module; for *docs and specs* she contributes files -in-tree under `contributions/module-name/`. See -[CONTRIBUTING](docs/CONTRIBUTING.md) for how this works. +志愿者可自由选择任意模块，并按自己的节奏开展工作。 +对于*代码与仿真*模块，她在*自己的仓库*中开发软件包，并提交简短 PR 从模块处*链接*；对于*文档与规格*，她在 `contributions/module-name/` 下以树内（in-tree）方式贡献文件。具体做法请参阅 +[CONTRIBUTING](docs/CONTRIBUTING.md)。 -Multiple developers are welcome to work on the same module. -The best solution for each module surfaces over time, with the project master having the last call. +欢迎多位开发者同时参与同一模块。 +各模块的最优方案将随时间浮现，项目负责人拥有最终决定权。 -1. Pick a contribution from the [list below](#requests-for-contributions). -2. [Let us know](https://github.com/makerspet/oomwoo/discussions) you're working on it and your progress. -3. Check [ARCHITECTURE.md](docs/ARCHITECTURE.md) and - [SOFTWARE_INTERFACES.md](docs/SOFTWARE_INTERFACES.md) for the system design - and ROS2 interfaces. +1. 从[下方列表](#requests-for-contributions)中选择一个贡献项。 +2. [告知我们](https://github.com/makerspet/oomwoo/discussions) 你的工作项及进展。 +3. 查阅 [ARCHITECTURE.md](docs/ARCHITECTURE.md) 和 + [SOFTWARE_INTERFACES.md](docs/SOFTWARE_INTERFACES.md) 了解系统设计与 ROS2 接口。 -## Requests for Contributions +## 贡献征集 -Every module below is *actionable now* — build it against the Gazebo simulation -([oomwoo-one](https://github.com/makerspet/oomwoo-one)) or a real *placeholder robot* -(a [Proscenic M6 Pro connected to ROS2](https://makerspet.com/blog/tutorial-connect-robot-vacuum-cleaner-to-ros-2-proscenic-m6-pro/)), -until OOMWOO hardware is ready. Pick one, tell us in -[Discussions](https://github.com/makerspet/oomwoo/discussions), build it in your own -repo (docs and specs go in-tree), and send a short PR linking it from the module. +以下每个模块*现在即可动手*——可基于 Gazebo 仿真 +([oomwoo-one](https://github.com/makerspet/oomwoo-one)) 或真实的*占位机器人* +（一款[已接入 ROS2 的 Proscenic M6 Pro](https://makerspet.com/blog/tutorial-connect-robot-vacuum-cleaner-to-ros-2-proscenic-m6-pro/)), +直到 OOMWOO 硬件就绪。择一开工，在 +[Discussions](https://github.com/makerspet/oomwoo/discussions), 中告知我们，在你的自有仓库中搭建（文档与规格以树内方式贡献），并提交简短 PR 从模块处链接。 -| Module | ID | Status | Notes | +| 模块 | ID | 状态 | 备注 | |---|---|---|---| -| ROS2 URDF + Gazebo sim | [urdf-gazebo-sim](./contributions/urdf-gazebo-sim) | In progress | Placeholder URDF + Gazebo sim (reference: [oomwoo-one](https://github.com/makerspet/oomwoo-one); [@alvarosamudio](https://github.com/alvarosamudio/oomwoo_gazebo) featured), refined when hardware lands | -| First clean: coverage + mapping + exploration | [clean-and-map](./contributions/clean-and-map) | Ready to start work | Coverage cleaning while SLAM-mapping and exploring | -| Auto cleaning | | In progress | Clean the entire room using an existing map (using coverage path planning) | -| Regression tests | | In progress | Set up simulatior regression test framework (auto cleaning in Gazebo) | -| Localization & navigation on a known map | [nav-localize](./contributions/nav-localize) | In progress | Nav2 nav, AMCL localization, relocalize when lost, resume map | -| Dock cycle: undock, dock, recharge | [dock-cycle](./contributions/dock-cycle) | Ready to start work | Undock, return-to-dock, precise docking, station services, find dock when lost | -| Recovery behaviors & safety | [recovery-safety](./contributions/recovery-safety) | Ready to start work | Recovery ladder, escalation, pause-and-alert, safety sensors, status reporting | -| Compute benchmark & memory reduction | [compute-benchmark](./contributions/compute-benchmark) | In progress | Measure ROS2/Nav2/SLAM memory, compare composable nodes, and track the 4 GB -> 2 GB target | -| Floor-surface handling & edge cleaning | [floor-care](./contributions/floor-care) | Ready to start work | Wall/edge following, carpet vs hardwood, mop lift/lower | -| Cleaning modes, zones & job orchestration | [cleaning-jobs](./contributions/cleaning-jobs) | Ready to start work | Modes (regular/spot), virtual walls, room segmentation, job splitting + resume | -| Live robot bring-up & validation | [live-robot-bringup](./contributions/live-robot-bringup) | Ready to start work | Connect the placeholder Proscenic M6 Pro to ROS2, re-run sim tests on hardware | -| Source 3D models (STEP) for BOM parts | [source-3d-models](./contributions/source-3d-models) | In progress | Obtain / measure / model STEP files of off-the-shelf parts (wheels, fans, caster…) so mounts fit | -| Procure part specs & datasheets | [part-specs](./contributions/part-specs) | In progress | Find/measure/reverse-engineer specs (pinouts, encoder PPR, torque, how to drive fans…) for sourced parts | -| I/O + motor-driver PCB | [io-pcb](./contributions/io-pcb) | In progress | I/O board with CM4/CM5 socket, STM32G070 MCU - motors, sensors, 4S2P charging, safety, FreeRTOS, custom serial to CM4/CM5, 2D LiDAR header, IMU, audio serial/amp/speaker, MIPI camera(s) i/f; KiCad, JLCPCB | -| Fit software into 2GB RAM | [compute-benchmark](./contributions/compute-benchmark) | In progress | ROS2 node composition, Rust; remove Gazebo, desktop UI | +| ROS2 URDF + Gazebo sim | [urdf-gazebo-sim](./contributions/urdf-gazebo-sim) | 进行中 | 占位 URDF + Gazebo 仿真（参考：[oomwoo-one](https://github.com/makerspet/oomwoo-one); [@alvarosamudio](https://github.com/alvarosamudio/oomwoo_gazebo) 精选），硬件落地后细化 | +| 首次清扫：覆盖 + 建图 + 探索 | [clean-and-map](./contributions/clean-and-map) | 可开始工作 | 在 SLAM 建图与探索的同时进行覆盖清扫 | +| 自动清扫 | | 进行中 | 使用已有地图清扫整个房间（采用覆盖路径规划） | +| 回归测试 | | 进行中 | 搭建仿真器回归测试框架（Gazebo 中的自动清扫） | +| 已知地图上的定位与导航 | [nav-localize](./contributions/nav-localize) | 进行中 | Nav2 导航、AMCL 定位、丢失后重定位、恢复地图 | +| 回充循环：离桩、回桩、充电 | [dock-cycle](./contributions/dock-cycle) | 可开始工作 | 离桩、返回充电座、精准对接、充电座服务、丢失后寻桩 | +| 恢复行为与安全 | [recovery-safety](./contributions/recovery-safety) | 可开始工作 | 恢复阶梯、升级机制、暂停告警、安全传感器、状态上报 | +| 算力基准与内存优化 | [compute-benchmark](./contributions/compute-benchmark) | 进行中 | 测量 ROS2/Nav2/SLAM 内存占用，对比可组合节点，跟踪 4 GB -> 2 GB 目标 | +| 地面材质处理与沿边清扫 | [floor-care](./contributions/floor-care) | 可开始工作 | 沿墙/沿边行驶、地毯与硬木地板区分、拖布升降 | +| 清扫模式、分区与任务编排 | [cleaning-jobs](./contributions/cleaning-jobs) | 可开始工作 | 模式（常规/定点）、虚拟墙、房间分割、任务拆分与续扫 | +| 实机启动与验证 | [live-robot-bringup](./contributions/live-robot-bringup) | 可开始工作 | 将占位用 Proscenic M6 Pro 接入 ROS2，在硬件上复现仿真测试 | +| 为 BoM 零件采集 3D 模型（STEP） | [source-3d-models](./contributions/source-3d-models) | 进行中 | 获取/测量/建模市售零件（轮子、风扇、万向轮等）的 STEP 文件，确保支架匹配 | +| 采购零件规格与数据手册 | [part-specs](./contributions/part-specs) | 进行中 | 查找/测量/逆向工程所采零件的规格（引脚定义、编码器 PPR、扭矩、风扇驱动方式等） | +| I/O + 电机驱动 PCB | [io-pcb](./contributions/io-pcb) | 进行中 | 带 CM4/CM5 插座的 I/O 板，STM32G070 MCU——电机、传感器、4S2P 充电、安全、FreeRTOS、与 CM4/CM5 的自定义串口、2D LiDAR 接头、IMU、音频串口/功放/扬声器、MIPI 摄像头接口；KiCad、JLCPCB | +| 将软件适配至 2GB RAM | [compute-benchmark](./contributions/compute-benchmark) | 进行中 | ROS2 节点组合、Rust；移除 Gazebo、桌面 UI | -> Planned and on-hold modules (mechanical design, later-phase software) live in the -> [RFC backlog](docs/RFC_BACKLOG.md). +> 规划中及暂缓的模块（机械设计、后期软件）收录于 +> [RFC 待办清单](docs/RFC_BACKLOG.md)。 -## Source code reference +## 源代码参考 -- [OOMWOO ROS2 and Ubuntu installation](https://github.com/makerspet/oomwoo-install/) source code -- [OOMWOO ROS2 URDF package and config](https://github.com/makerspet/oomwoo_urdf/) source code -- [remakeai reference vacuum teardown](https://github.com/remakeai/vacuum-cleaner-teardown) — a consumer LiDAR vacuum with a basic dock and stationary mop. +- [OOMWOO ROS2 与 Ubuntu 安装](https://github.com/makerspet/oomwoo-install/) 源代码 +- [OOMWOO ROS2 URDF 包与配置](https://github.com/makerspet/oomwoo_urdf/) 源代码 +- [remakeai 参考扫地机拆解](https://github.com/remakeai/vacuum-cleaner-teardown) —— 一款带基础充电座和固定拖布的商用 LiDAR 扫地机。 -## Related prior art +## 相关先行作品 -- [AlieksieievYurii/vacuum-cleaner](https://github.com/AlieksieievYurii/vacuum-cleaner) — a DIY 3D-printed robot vacuum (Raspberry - Pi Zero W, gyroscope-based, Fusion 360, Android control app, no dock) -- [kaiaai/LDS](https://github.com/kaiaai/LDS), [kaiaai/lds2d](https://github.com/kaiaai/lds2d) — open-source 2D LiDAR libraries (C++, Python) supporting 23+ LiDAR models -- [remakeai/vacuum_ros2_bridge](https://github.com/remakeai/vacuum_ros2_bridge) — ROS2 bridge for a 3irobotix CRL-200-based vacuum (Proscenic), full ROS2 control -- [Valetudo](https://github.com/Hypfer/Valetudo) — cloud-free firmware replacement for commercial vacuums (local app-level control, not ROS2) -- [Dennis Giese / robotinfo.dev](https://robotinfo.dev) — teardowns and rootability of commercial robot vacuums. -- [codetiger/VacuumTiger](https://github.com/codetiger/VacuumTiger) - 3irobotix CRL-200-based vacuum low-level control reverse engineered -- [Build a ROS2/LiDAR robot crash course](https://makerspet.com/blog/build-arduino-self-driving-robot-video-instructions/) - watch this if you have no robotics experience -- [Open Mower](openmower.de) - open-source outdoor lawn mower +- [AlieksieievYurii/vacuum-cleaner](https://github.com/AlieksieievYurii/vacuum-cleaner) — 一款 DIY 3D 打印扫地机器人（Raspberry Pi Zero W，基于陀螺仪，Fusion 360，Android 控制应用，无充电座） +- [kaiaai/LDS](https://github.com/kaiaai/LDS), [kaiaai/lds2d](https://github.com/kaiaai/lds2d) — 开源 2D LiDAR 库（C++、Python），支持 23+ 种 LiDAR 型号 +- [remakeai/vacuum_ros2_bridge](https://github.com/remakeai/vacuum_ros2_bridge) — 基于 3irobotix CRL-200 的扫地机器人（Proscenic）ROS2 桥接，完整 ROS2 控制 +- [Valetudo](https://github.com/Hypfer/Valetudo) — 商用扫地机器人的免云端固件替代方案（本地应用级控制，非 ROS2） +- [Dennis Giese / robotinfo.dev](https://robotinfo.dev) — 商用扫地机器人的拆解与 root 可行性分析。 +- [codetiger/VacuumTiger](https://github.com/codetiger/VacuumTiger) - 基于 3irobotix CRL-200 的扫地机器人底层控制逆向工程 +- [Build a ROS2/LiDAR robot crash course](https://makerspet.com/blog/build-arduino-self-driving-robot-video-instructions/) - 若无机器人经验可看此教程 +- [Open Mower](openmower.de) - 开源户外割草机 -## Design research +## 设计调研 -We reviewed the 2025–2026 consumer robot vacuum landscape (global + China-sourceable -brands, all price tiers) to decide which solutions to copy and which to skip. Key -takeaways for the build: +我们调研了 2025–2026 年消费级扫地机器人市场格局（全球 + 中国可采购品牌，各价位段），以决定哪些方案值得借鉴、哪些可以跳过。对本项目构建的关键结论： -- *Suction is a sourcing problem, not an engineering one.* Real-world cleaning does - *not* track advertised suction (Pa); ~$500 mid-tier models beat flagships. A - moderate *sealed* sourced motor + a good brush + tight airflow sealing matches - flagships — *no custom impeller needed.* -- *"Never gets stuck" needs camera + AI sensor fusion*, not LiDAR alone — LiDAR is - blind below its ~10 cm turret (cables, socks). v1 leans on the *bumper* for low - obstacles; vision-based avoidance is a later / experimental goal, not an MVP promise. -- *Anti-tangle brush:* a *tapered rubber roller* resists hair-wrap best (a top user - complaint) and is easy to 3D-print. -- *Mop:* a 3D-printed *dual-spinning* mop is competitive; the self-washing roller - mop's edge is overstated and hard to replicate — skip it for now. +- *吸力是采购问题，而非工程问题。* 实际清洁效果*并不*与宣传的吸力（Pa）成正比；约 500 美元的中端机型往往胜过旗舰款。一台适中的*密封*外购电机 + 优质滚刷 + 严密的气流密封，即可媲美旗舰 —— *无需定制叶轮。* +- *「永不卡住」需要摄像头 + AI 传感器融合*，单靠 LiDAR 不够 —— LiDAR 对其约 10 cm 云台以下区域是盲的（电线、袜子等）。v1 主要依赖*防撞条*应对低矮障碍；基于视觉的避障是后续/实验性目标，并非 MVP 承诺。 +- *防缠绕刷：* *锥形橡胶滚刷*最能抵抗毛发缠绕（用户头号抱怨之一），且易于 3D 打印。 +- *拖地：* 3D 打印的*双旋转*拖布已具竞争力；自清洗滚刷拖地的优势被夸大且难以复现 —— 现阶段先跳过。 -*Well-loved models worth studying:* Eufy Omni S2 (obstacle avoidance), Narwal Flow -(roller mop), Ecovacs Deebot T90 Pro Omni (~$499 all-rounder), Dreame X40 Ultra -(dual-spinning mop). *Dreame* is also the most [Valetudo](https://github.com/Hypfer/Valetudo)-rootable -brand — the safest donor to study. *(Per-model rankings are directional, from -single-run reviewer tests.)* +*值得研究的口碑机型：* Eufy Omni S2（避障）、Narwal Flow（滚刷拖地）、Ecovacs Deebot T90 Pro Omni（约 499 美元全能型）、Dreame X40 Ultra（双旋转拖布）。*Dreame* 也是与 [Valetudo](https://github.com/Hypfer/Valetudo)-rootable 兼容度最高的品牌 —— 最安全的拆解研究对象。*(各机型排名仅供参考，来自单次评测测试。)* -## About +## 关于 -The project name "OOMWOO" is a rotational ambigram - it reads the same flipped 180°, like the robot itself, roaming your floor in every direction. +项目名称 "OOMWOO" 是一个旋转对称字（rotational ambigram）—— 旋转 180° 后读法相同，就像机器人本身，朝各个方向在你家地板上漫游。 -The project is sponsored by makerspet.com and remake.ai. We are reusing their open-source solutions. -- If you'd rather skip the parts hunt, a kit (motors, PCB, brushes, gaskets, LiDAR) will be available at [makerspet.com](https://makerspet.com), from the same maker behind this project. The kit is a convenience, never a requirement. *Everything here stays open.* -- When we get to apps, [remake.ai](https://remake.ai) will be providing its robot apps platform and app store. Using the app store will be entirely optional. The vacuum will *always support cloud-free, local operation for regular functionality out-of-the-box*. +本项目由 makerspet.com 和 remake.ai 赞助。我们正在复用他们的开源方案。 +- 若你不想四处搜罗零件，可在 [makerspet.com](https://makerspet.com), 购买套件（电机、PCB、滚刷、垫圈、LiDAR），提供方即本项目作者。套件仅为便利选项，绝非必需。*此处一切内容均保持开源。* +- 待开发应用时，[remake.ai](https://remake.ai) 将提供其机器人应用平台与应用商店。是否使用应用商店完全可选。扫地机器人将*始终开箱即支持免云端、本地运行，满足日常功能需求*。 -## License +## 许可证 -Code is released under the [Apache License 2.0](LICENSE). +代码以 [Apache License 2.0](LICENSE) 发布。 -Hardware design files, once added, to be released under an open hardware -license (TBD). +硬件设计文件（待添加）将以开放硬件许可证发布（待定）。